output.contains "Resolved: lib-1.9.jar"

        where:
        dsl << ['groovy', 'kotlin']
    }

    @UsesSample("dependencyManagement/customizingResolution-selectionRule")
    def "can run targeted rule sample with #dsl dsl"() {
        executer.inDirectory(sample.dir.file(dsl))

        when:
        run "printTargetConfig"

        then:
        output.contains "Resolved: api-1.4.jar"

        where:

// The output Runtime ops depends on both Device Type and Runtime Host.
//
// Input:
//     Tensorflow Dialect MLIR with tf_device.cluster ops and virtual devices.
//     xla_device_type - The device type that is being targeted.
// Output:
//     Tensorflow Dialect MLIR with Runtime specific ops. All tf_device.cluster
//     ops are removed. Physical devices are assigned to ops instead of virtual
//     devices.

            apply type: RulePlugin
        '''

        then:
        succeeds "echo"

        and:
        output.contains('value: foo')
    }

    def "unmanaged property of managed type can be targeted by rules"() {
        when:
        buildScript '''
            @Managed
            interface Platform {
                @Unmanaged
                OperatingSystem getOperatingSystem()

 * }
 * </pre>
 * <p>
 * Note: the Gradle {@code "application"} plugin adds a pre-configured task of this type named {@code "startScripts"}.
 * <p>
 * The task generates separate scripts targeted at Microsoft Windows environments and UNIX-like environments (e.g. Linux, macOS).
 * The actual generation is implemented by the {@link #getWindowsStartScriptGenerator()} and {@link #getUnixStartScriptGenerator()} properties, of type

                    "ops."}];

  let options = [
    Option<"device_type_", "device-type", "std::string",
        /*default=*/"\"INVALID_DEVICE_TYPE\"",
        "The device type being targeted.">,
  ];

  let constructor = "mlir::mhlo::CreateTFXLADeviceSpecificTransformsPass()";
}

def InfeedOpsXlaAdjustLayout : Pass<"infeed-ops-xla-adjust-layout",

     */
    @Variant
    Flavor getFlavor();

    /**
     * Returns the {@link org.gradle.nativeplatform.platform.NativePlatform} that this binary is targeted to run on.
     */
    @Variant
    NativePlatform getTargetPlatform();

    /**
     * Returns the {@link org.gradle.nativeplatform.BuildType} used to construct this binary.
     */
    @Variant

import org.gradle.test.preconditions.UnitTestPreconditions

// NB: there's nothing specific about Java support and continuous.
//     this spec just lays out some more practical use cases than the other targeted tests.
class SimpleJavaContinuousIntegrationTest extends AbstractContinuousIntegrationTest {

    def setup() {
        buildFile << """
            apply plugin: 'java'
        """
    }

		// where "go mod tidy" and "go list -m -u all" fight over whether the go.sum
		// should be considered up-to-date. The fix for now is to always treat the
		// go.sum as up-to-date during list -m -u. Probably the right fix is more targeted,
		// but in general list -u is looking up other checksums in the checksum database
		// that won't be necessary later, so it makes sense not to write the go.sum back out.
		if !ExplicitWriteGoMod && mode&ListU == 0 {

	// by the fact that only one SIGPROF can be handled by the
	// process at a time. If not, this lock will serialize those too.
	// The use of timer_create(2) on Linux to request process-targeted
	// signals may have changed this.)
	for !prof.signalLock.CompareAndSwap(0, 1) {
		// TODO: Is it safe to osyield here? https://go.dev/issue/52672
		osyield()
	}

The JVM running the Tooling API client and the one running the daemon can be different.
At the same time, classes that are sent to the build via custom build actions need to be targeted to the lowest supported Java version.
The JVM versions supported by Gradle is version-specific.
The upper bound is defined in the <<compatibility.adoc#compatibility,compatibility matrix>>.